research-article

SMALTA: practical and near-optimal FIB aggregation

Authors:

Zartash Afzal Uzmi,

Paul FrancisAuthors Info & Claims

CoNEXT '11: Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies

Article No.: 29, Pages 1 - 12

https://doi.org/10.1145/2079296.2079325

Published: 06 December 2011 Publication History

Abstract

IP Routers use sophisticated forwarding table (FIB) lookup algorithms that minimize lookup time, storage, and update time. This paper presents SMALTA, a practical, near-optimal FIB aggregation scheme that shrinks forwarding table size without modifying routing semantics or the external behavior of routers, and without requiring changes to FIB lookup algorithms and associated hardware and software. On typical IP routers using the FIB lookup algorithm Tree Bitmap, SMALTA shrinks FIB storage by at least 50%, representing roughly four years of routing table growth at current rates. SMALTA also reduces average lookup time by 25% for a uniform traffic matrix. Besides the benefits this brings to future routers, SMALTA provides a critical easy-to-deploy one-time benefit to the installed base should IPv4 address depletion result in increased routing table growth rate. The effective cost of this improvement is a sub-second delay in inserting updates into the FIB once every few hours. We describe SMALTA, prove its correctness, measure its performance using data from a Tier-1 provider as well as Route-Views. We also describe an implementation in Quagga that demonstrates its ease of implementation.

References

[1]

H. Ballani, P. Francis, T. Cao, and J. Wang. Making Routers Last Longer with ViAggre. In Procedings of USENIX NSDI, 2009.

Digital Library

[2]

A. Basu and G. Narlikar. Fast Incremental Updates for Pipelined Forwarding Engines. In Proceedings of IEEE Infocom, 2003.

[3]

M. Degermark, A. Brodnik, S. Carlsson, and S. Pink. Small Forwarding Tables for Fast Routing Lookups. In Procedings of SIGCOMM, 1997.

Digital Library

[4]

R. P. Draves, C. King, S. Venkatachary, and B. D. Zill. Constructing Optimal IP Routing Tables. In Proceedings of IEEE Infocom, volume 1, pages 88--97, March 1999.

[5]

W. Eatherton, Z. Dittia, and G. Varghese. Tree Bitmap: Hardware/Software IP Lookups with Incremental Updates. ACM SIGCOMM Compter Communication Review, 34(2):97--122, 2004.

Digital Library

[6]

J. Hasan, S. Cadambi, V. Jakkula, and S. T. Chakradhar. Chisel: A Storage-efficient, Collision-free Hash-based Network Processing Architecture. In Procedings of ISCA, 2006.

Digital Library

[7]

J. Hasan and T. N. Vijaykumar. Dynamic Pipelining: Making IP-Lookup Truly Scalable. In Procedings of SIGCOMM, 2005.

Digital Library

[8]

W. Herrin (Original Poster). Opportunistic Topological Aggregation in the RIB-->FIB Calculation? http://www.ops.ietf.org/lists/rrg/2008/threads.html#01880.

[9]

Y. Liu, X. Zhao, K. Nam, L. Wang, and B. Zhang. Incremental Forwarding Table Aggregation. In Proceedings of IEEE Globecom, 2010.

[10]

J. Moy, P. Pillay-Esnault, and A. Lindem. Graceful OSPF Restart. http://www.ietf.org/rfc/rfc3623, 2003.

Digital Library

[11]

Next Generation BGP Monitor. http://bgpmon.netsec.colostate.edu.

[12]

Quagga. Routing Suite. http://www.quagga.net/.

[13]

S. J. Richardson. Vertical Aggregation: A Strategy for FIB Reduction (Internet Draft). http://tools.ietf.org/html/draft-richardson-fib-reduction-00, 1996.

[14]

Routeviews. Project Page. http://www.routeviews.org/.

[15]

S. R. Sangli, E. Chen, R. Fernando, J. G. Scudder, and Y. Rekhter. Graceful Restart Mechanism for BGP. http://www.ietf.org/rfc/rfc4724, 2007.

[16]

J. Scudder. Communication on IETF WG (GROW) Mailing List. http://www.ietf.org/mail-archive/web/grow/current/msg01592.html, 2009.

[17]

S. Sikka and G. Varghese. Memory-Efficient State Lookups with Fast Updates. In Procedings of SIGCOMM, 2000.

Digital Library

[18]

A. Tariq, S. Jawad, and Z. Uzmi. TaCo: Semantic Equivalence of IP Prefix Tables. In Proceedings of IEEE ICCCN, 2011.

[19]

Z. Uzmi, A. Tariq, and P. Francis. FIB Aggregation with SMALTA (Internet Draft). http://tools.ietf.org/html/draft-uzmi-smalta-01, 2011.

[20]

Z. Uzmi et. al. Practical and Near-Optimal FIB Aggregation using SMALTA (Tech Report). http://www.mpi-sws.org/~zartash/TR-MPI-SMALTA.pdf, 2011.

[21]

B. Zhang, L. Wang, X. Zhao, Y. Liu, and L. Zhang. FIB Aggregation (Internet Draft). http://tools.ietf.org/html/draft-zhang-fibaggregation-02, 2009.

[22]

X. Zhao, Y. Liu, L. Wang, and B. Zhang. On the Aggregatability of Router Forwarding Tables. In Proceedings of IEEE Infocom, 2010.

Digital Library

Cited By

Lu JZhao HQi YFeng YGuo XLi SSong EWei XLyu BWen RZhu S(2024)QuarkTable: Building Compact Forwarding Tables for Programmable Switches on Public CloudsProceedings of the 8th Asia-Pacific Workshop on Networking10.1145/3663408.3663415(45-51)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.1145/3663408.3663415
Koch TYu SAgarwal SKatz-Bassett EBeckett RSchulzrinne HKohler EMaltz DMisra V(2023)PAINTER: Ingress Traffic Engineering and Routing for Enterprise Cloud NetworksProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604868(360-377)Online publication date: 10-Sep-2023
https://dl.acm.org/doi/10.1145/3603269.3604868
Zhang MLi GKong XLiu CXu MGu GWu J(2023)NetHCF: Filtering Spoofed IP Traffic With Programmable SwitchesIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.316101520:2(1641-1655)Online publication date: 1-Mar-2023
https://doi.org/10.1109/TDSC.2022.3161015
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SMALTA: practical and near-optimal FIB aggregation
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Published In

cover image ACM Conferences

CoNEXT '11: Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies

December 2011

364 pages

ISBN:9781450310413

DOI:10.1145/2079296

General Chairs:
Kenjiro Cho
IIJ/Keio University, Japan
,
Mark Crovella
Boston University

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

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Published: 06 December 2011

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Co-NEXT '11

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SIGCOMM

Co-NEXT '11: Conference on emerging Networking Experiments and Technologies

December 6 - 9, 2011

Tokyo, Japan

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Overall Acceptance Rate 198 of 789 submissions, 25%

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Cited By

Lu JZhao HQi YFeng YGuo XLi SSong EWei XLyu BWen RZhu S(2024)QuarkTable: Building Compact Forwarding Tables for Programmable Switches on Public CloudsProceedings of the 8th Asia-Pacific Workshop on Networking10.1145/3663408.3663415(45-51)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.1145/3663408.3663415
Koch TYu SAgarwal SKatz-Bassett EBeckett RSchulzrinne HKohler EMaltz DMisra V(2023)PAINTER: Ingress Traffic Engineering and Routing for Enterprise Cloud NetworksProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604868(360-377)Online publication date: 10-Sep-2023
https://dl.acm.org/doi/10.1145/3603269.3604868
Zhang MLi GKong XLiu CXu MGu GWu J(2023)NetHCF: Filtering Spoofed IP Traffic With Programmable SwitchesIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.316101520:2(1641-1655)Online publication date: 1-Mar-2023
https://doi.org/10.1109/TDSC.2022.3161015
Li QWu YDuan JYang JJiang Y(2022)Weighted NSFIB Aggregation With Generalized Next Hop of Strict Partial OrderIEEE Transactions on Network and Service Management10.1109/TNSM.2022.315038919:2(890-904)Online publication date: Jun-2022
https://doi.org/10.1109/TNSM.2022.3150389
Michel OBifulco RRétvári GSchmid S(2021)The Programmable Data PlaneACM Computing Surveys10.1145/344786854:4(1-36)Online publication date: 3-May-2021
https://dl.acm.org/doi/10.1145/3447868
Wan YSong HChe HXu YWang YZhang CWang ZPan TLi HJiang HHu CLiu B(2021)FastUp: Fast TCAM Update for SDN Switches in Datacenter Networks2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS51616.2021.00089(887-897)Online publication date: Jul-2021
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Islam MKhan J(2021)CP-Trie: Cumulative PopCount based Trie for IPv6 Routing Table Lookup in Software and ASIC2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)10.1109/HPSR52026.2021.9481816(1-8)Online publication date: 7-Jun-2021
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Grigoryan GLiu YKwon M(2020)PFCA: A Programmable FIB Caching ArchitectureIEEE/ACM Transactions on Networking10.1109/TNET.2020.3001904(1-13)Online publication date: 2020
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Grigoryan GLiu YBenson TZilberman N(2018)PFCAProceedings of the 2018 Symposium on Architectures for Networking and Communications Systems10.1145/3230718.3230721(97-103)Online publication date: 23-Jul-2018
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